Identifying cellular and molecular signatures from distinct T cell receptor clonotypes associated with favorable immune checkpoint inhibitor responses in HNSCCs

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Project Summary/Abstract Cancer immunotherapy has become one of the pillar therapies in treating cancer patients, exemplified by immune checkpoint inhibitors (ICI) (e.g., anti-PD1). While ICIs have significantly improved the prognosis of cancer patients, the response rate to ICI monotherapy remains low (10-20%) for many types of cancer, such as head and neck squamous cell carcinoma (HNSCC). Some variability may be explained by human papillomavirus (HPV)- vs. carcinogen-induced, tumor antigen-specific T cell responses in HPV+ or HPV− HNSCC, reflecting a unique disease opportunity to investigate ICI responsiveness. Thus, it is vital to better understand the mechanisms underlying heterogenous responses to ICI and to identify new targets that may sensitize HNSCCs to mono- and combination immunotherapy. In this application, we propose to focus on T cell phenotypes associated with clinical response, dynamic changes in specific T cell receptor (TCR) clonotypes, and TCR clonotype-specific transcriptomic changes in response to ICI treatment, using HNSCC patient samples from an ongoing clinical trial at our institution and detailed studies using murine HNSCC models. Using HCC 18-139 trial samples, we will compare tumor infiltrating lymphocytes (TIL) and peripheral blood lymphocytes (PBL) from pre- and post-treatment samples and examine TCR dynamics and T cell phenotypes in blood (minimally invasive and readily accessible) and in tumors in the context of ICI-induced anti-tumor immunity. Our mouse model allows functional validation among distinct TCR clonotypes correlating with ICI responses, and permits manipulation of novel potential targets to enhance clinical responsiveness as well as lay the groundwork for future clinical trials. Our proposed studies will identify cellular and molecular markers to better predict ICI responses in HNSCC patients treated with different combinations of ICIs and would facilitate finding novel mechanisms of differential ICI responses using transcriptomic differences in distinct clonal TCR-bearing T cell populations. A unique strength of our proposal is integration of human clinical trial samples and mouse models as a more powerful platform to uncover mechanistic insights that are translatable into the clinical setting.